Methods and Systems for Inter-Layer Image Prediction Signaling

ABSTRACT

Embodiments of the present invention comprise systems and methods for predicting image elements.

FIELD OF THE INVENTION

Embodiments of the present invention comprise methods and systems forinter-layer image prediction signaling.

SUMMARY

Some embodiments of the present invention comprise methods and systemsfor prediction of images comprising multiple dynamic range layers. Someembodiments comprise methods and systems for communicating predictionvariables between an encoder and a decoder or transcoder.

The foregoing and other objectives, features, and advantages of theinvention will be more readily understood upon consideration of thefollowing detailed description of the invention taken in conjunctionwith the accompanying drawings.

BRIEF DESCRIPTION OF THE SEVERAL DRAWINGS

FIG. 1A is a chart showing an exemplary embodiment of the presentinvention comprising prediction with a scaled and offset LDR imageelement;

FIG. 1B is a chart showing an exemplary embodiment of the presentinvention comprising scaling and offsetting decoded image elements forHDR prediction;

FIG. 2 is a chart showing an exemplary embodiment of the presentinvention comprising conversion to an alternative color space;

FIG. 3 is a chart showing an exemplary embodiment of the presentinvention comprising scaling an LDR image element according to HDRbitstream data;

FIG. 4 is a chart showing an exemplary embodiment of the presentinvention comprising scaling and applying an offset to an LDR imageelement according to HDR bitstream data;

FIG. 5 is a chart showing an exemplary embodiment of the presentinvention comprising scaling LDR transform coefficients for HDRprediction;

FIG. 6 is a chart showing an exemplary embodiment of the presentinvention comprising applying an offset to LDR transform coefficientsfor HDR prediction;

FIG. 7 is a chart showing an exemplary embodiment of the presentinvention comprising scaling LDR transform coefficients and applying anoffset to LDR transform coefficients for HDR prediction;

FIG. 8 is a chart showing an exemplary embodiment of the presentinvention comprising scaling and applying an offset to color-transformedimage elements for HDR prediction; and

FIG. 9 is a chart showing an exemplary embodiment of the presentinvention comprising separate scaling and offset operations forluminance and chrominance elements.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

Embodiments of the present invention will be best understood byreference to the drawings, wherein like parts are designated by likenumerals throughout. The figures listed above are expressly incorporatedas part of this detailed description.

It will be readily understood that the components of the presentinvention, as generally described and illustrated in the figures herein,could be arranged and designed in a wide variety of differentconfigurations. Thus, the following more detailed description of theembodiments of the methods and systems of the present invention is notintended to limit the scope of the invention but it is merelyrepresentative of the presently preferred embodiments of the invention.

Elements of embodiments of the present invention may be embodied inhardware, firmware and/or software. While exemplary embodiments revealedherein may only describe one of these forms, it is to be understood thatone skilled in the art would be able to effectuate these elements in anyof these forms while resting within the scope of the present invention.

Some embodiments of the present invention comprise systems and methodsfor using the low dynamic range video sequence to predict the highdynamic range version of the image data. This may be referred to asinter-layer prediction in this application. Some embodiments of thepresent invention comprise a spatially-varying inter-layer predictionmechanism for HDR video coding. Some embodiments of the presentinvention comprise an inter-layer prediction mechanism for HDR videocoding that operates in the color spaces utilized for video compressionand transmission. Some embodiments utilize gamma corrected color spaces.Exemplary embodiments may utilize xvYCC and YCbCr color spaces. Someembodiments of the present invention comprise an inter-layer predictionmechanism for HDR video coding that may be disabled spatially. Someembodiments of the present invention comprise an inter-layer predictionmechanism for HDR video coding that is multiplication free. Someembodiments of the present invention comprise an inter-layer predictionmechanism for HDR video coding that can be utilized in a single-loopdecoder. Some embodiments may also be incorporated into multi-loopdesigns.

Embodiments of the present invention comprise an inter-layer predictiontechnique for high-dynamic range video coding. Some aspects of someembodiments comprise elements described in U.S. patent application Ser.No. 11/362,571 filed on Feb. 24, 2006, which is hereby incorporatedherein by reference. Some embodiments of the present invention comprisea method for projecting decoded low dynamic range data to the highdynamic range coding space. This process may be referred to asinter-layer prediction.

An analogous process to inter-layer prediction for high dynamic rangevideo coding is inter-layer prediction for bit-depth scalability. In theproblem for bit-depth scalability, the baselayer of a video bit-streamcontains a representation of the video sequence at a reduced bit-depth.For example, the baselayer may contain an eight-bit representation ofthe sequence, while the enhancement layer of the bit-stream may containa ten-bit representation. In some scenarios, more than two layers may beused. In some scenarios, an eight-bit version may represent the eightmost significant bits of the higher bit-depth sequence. The higherbit-depth version is therefore predicted by multiplying (or equivalentlyscaling) the decoded lower bit-depth data to the higher bit-depth. Inthis specific example, the eight-bit data would be decoded andsubsequently scaled by a factor of four to predict the ten-bit data.This scaling may be done in either the intensity or transform domain,depending on the application.

High dynamic range video coding can be a more general case of bit-depthscalability. The baselayer and enhancement layer may contain datarepresented with different bit-depths. However, the baselayer may not beconstrained to represent the most significant bits of the enhancementlayer data. In some embodiments of the present invention, the baselayerdata may contain a lower bit-depth representation of the high dynamicrange sequence, and this lower bit-depth may not always correspond tothe most significant bits of the corresponding higher bit-depthrepresentation.

Some embodiments of the present invention may be described withreference to FIG. 1A. In these embodiments, a high dynamic range (HDR)image is received 100. A corresponding low dynamic range (LDR) image mayalso be received 101 or created from the HDR image. The LDR image may becreated through a tone scale operation, a conversion function or someother method. The LDR image may then be predicted, transformed,quantized and encoded 102 as is well known in the art. In a fewexemplary embodiments the LDR image may be transformed using a discretecosine transform (DCT), a wavelet transform or by other commontransformation methods. The prediction, transformation, quantization andencoding processes may then be substantially reversed 103 to provide adecoded LDR image as would be decoded at a typical decoder. Typically, ade-quantization process is lossy and therefore does not produce an exactcopy of the originally encoded image. Other processes may also affectthe reproduction of the original LDR image. Regardless, the decoded LDRimage may be processed by one or more of the following methods: colorconversion, scaling 104 and offsetting 105. The decoded, processed LDRimage may now be used to create 106 a residual HDR image. This may beperformed by subtracting the decoded, processed LDR image from theoriginal HDR image. Other methods may also be used.

The residual HDR image may then be transformed, quantized and encoded107 or otherwise prepared for transmission to a destination. This stepmay comprise embedding the encoded residual HDR image into an HDR orenhancement layer bitstream. Information related to the colorconversion, scaling and offset operations may also be encoded andembedded 108 in the HDR or enhancement bitstream. The HDR/enhancementlayer bitstream may then be transmitted to a destination. AnLDR/baselayer bitstream may also be transmitted to the destination. TheLDR/baselayer bitstream may also comprise a transformed, quantized andencoded LDR image.

A decoder receiving the LDR/baselayer bitstream may then decode theLDR/baselayer image. A decoder receiving the LDR/baselayer bitstream andthe HDR/enhancement layer bitstream may decode both the LDR/baselayerimage and the HDR/enhancement layer image. Embodiments of the presentinvention comprise methods and systems for encoding and decoding imagesin this framework and similar scenarios.

Some embodiments of the present invention may be described withreference to FIG. 1B. In these embodiments, a baselayer decoder mayreceive baselayer data, such as from a baselayer bitstream 2. Thebaselayer decoder may decode 6 a baselayer block or other image elementand represent it in the spatial domain. Some embodiments may comprisefull decoding of the block, including a prediction process followed byresidual refinement. Some embodiments may comprise reconstruction of theresidual only. In some embodiments, the spatial information in thebaselayer may be utilized to predict the high dynamic range signal. Someembodiments may comprise scaling 7 the baselayer information. Someembodiments may also comprise adding an offset 8 to the baselayerinformation. Some embodiments may comprise both scaling 7 and adding anoffset 8. Once scaling 7 and/or adding an offset 8 are performed on thedecoded baselayer information, that scaled, offset information may beused to predict 9 an enhancement layer, such as a higher dynamic range(HDR) layer. In some embodiments, scaling 7 and offset 8 data may beextracted from an enhancement layer 4 bitstream. In some embodiments,subsequent refinement may be decoded from the enhancement layerbit-stream 4.

Some embodiments of the present invention may be described withreference to FIG. 2. In these embodiments, a decoder may receivebaselayer data 10 from which a block or other image element may bedecoded 12 into spatial image data. This spatial image data may then beconverted 13 to an alternative color space. This converted data may thenbe scaled 14 and/or offset 15. Scaling and offset operations may beperformed according to instructions and/or data received from anenhancement bitstream 11. This converted, scaled and/offset data maythen be converted 16 back to the coding color space. Once converted backto the coding color space, the scaled and/or offset data may be used topredict 17 an enhancement layer, such as a higher dynamic range (HDR)layer.

Some embodiments of the present invention may be described withreference to FIG. 3. In these embodiments, an LDR/baselayer image isreceived 30 and corresponding HDR/enhancement layer data is alsoreceived 31. An LDR/baselayer block or image element is then decoded 32from the LDR/baselayer image. The decoded LDR/baselayer image element isthen scaled 33. This scaling may be performed according to data embeddedin the HDR/enhancement layer data. Scaling of individual image elementsmay be related to or a function of image characteristics comprisingspatial location, luminance data, chrominance data and other data. Thescaled, decoded LDR/baselayer image may then be used to predict 34 acorresponding HDR block or image element. In some embodiments, thescaled, decoded LDR/baselayer image element may be added to acorresponding decoded residual image element to form an HDR/enhancementlayer image element.

Some embodiments of the present invention may be described withreference to FIG. 4. In these embodiments, an LDR/baselayer image isreceived 40 and corresponding HDR/enhancement layer data is alsoreceived 41. An LDR/baselayer block or image element is then decoded 42from the LDR/baselayer image. The decoded LDR/baselayer image element isthen scaled 43. This scaling may be performed according to data embeddedin the HDR/enhancement layer data. Scaling of individual image elementsmay be related to or a function of image characteristics comprisingspatial location, luminance data, chrominance data and other data. Anoffset may then be added 44 to the scaled LDR image element. Offset datamay be carried in the corresponding HDR/enhancement layer data. Offsetdata may vary between image elements and may be dependent on imagecharacteristics comprising spatial location, luminance data, chrominancedata and other data.

The scaled, offset and decoded LDR/baselayer image may then be used topredict 45 a corresponding HDR block or image element. In someembodiments, the scaled, offset and decoded LDR/baselayer image elementmay be added to a corresponding decoded residual image element to forman HDR/enhancement layer image element.

Some embodiments of the present invention may be described withreference to FIG. 5. In these embodiments, an LDR/baselayer imagecomprising LDR transform coefficients is received 50 and correspondingHDR/enhancement layer data is also received 51. The LDR/baselayer imagetransform coefficients may then be scaled 52. This scaling may beperformed according to data embedded in the HDR/enhancement layer data.Scaling of LDR transform coefficients may be related to or a function ofimage characteristics comprising spatial location, luminance data,chrominance data and other data. The scaled LDR/baselayer transformcoefficients may then be used to predict 53 transform coefficients for acorresponding HDR block or image element.

Some embodiments of the present invention may be described withreference to FIG. 6. In these embodiments, an LDR/baselayer imagecomprising LDR transform coefficients is received 60 and correspondingHDR/enhancement layer data is also received 61. The LDR/baselayer imagetransform coefficients may then be offset 62. Offset data may be carriedin the corresponding HDR/enhancement layer data 61. Offset data may varybetween image elements and may be dependent on image characteristicscomprising spatial location, luminance data, chrominance data and otherdata. The offset LDR/baselayer transform coefficients may then be usedto predict 63 transform coefficients for a corresponding HDR block orimage element.

Some embodiments of the present invention may be described withreference to FIG. 7. In these embodiments, an LDR/baselayer imagecomprising LDR transform coefficients is received 70 and correspondingHDR/enhancement layer data is also received 71. The LDR/baselayer imagetransform coefficients may then be scaled 72. This scaling may beperformed according to data embedded in the HDR/enhancement layer data.Scaling of LDR transform coefficients may be related to or a function ofimage characteristics comprising spatial location, luminance data,chrominance data and other data. The scaled LDR/baselayer imagetransform coefficients may then be offset 73. Offset data may be carriedin the corresponding HDR/enhancement layer data 71. Offset data may varybetween image elements and may be dependent on image characteristicscomprising spatial location, luminance data, chrominance data and otherdata. The scaled, offset LDR/baselayer transform coefficients may thenbe used to predict 74 transform coefficients for a corresponding HDRblock or image element.

Some embodiments of the present invention may be described withreference to FIG. 8. In these embodiments, an LDR/baselayer image isreceived 80 and corresponding HDR/enhancement layer data is alsoreceived 81. An LDR/baselayer block or image element is then decoded 82from the LDR/baselayer image. The decoded LDR/baselayer image elementmay then be converted 83 or transformed to an alternative color formator color space. While in this alternative color space, the LDR imageelement may be scaled 84. This scaling may be performed according todata embedded in the HDR/enhancement layer data. Scaling of individualimage elements may be related to or a function of image characteristicscomprising spatial location, luminance data, chrominance data and otherdata. Also, while in the alternative color space, an offset may then beadded 85 to the scaled, color-converted LDR image element. Offset datamay be carried in the corresponding HDR/enhancement layer data. Offsetdata may vary between image elements and may be dependent on imagecharacteristics comprising spatial location, luminance data, chrominancedata and other data.

The scaled and/or offset and color-converted LDR/baselayer image maythen be converted back 86 to the coding color space. This scaled and/oroffset, coding-color-space LDR/baselayer image may then be used topredict 87 a corresponding HDR block or image element.

Some embodiments of the present invention may be described withreference to FIG. 9. In these embodiments, an LDR/baselayer image isreceived 90 and corresponding HDR/enhancement layer data is alsoreceived 91. An LDR/baselayer block or image element may then be decoded92 from the LDR/baselayer image. In these embodiments, the decodedLDR/baselayer image may comprise separable luminance and chrominancevalues. In some embodiments, luminance values may be scaled 93 inrelation to their spatial position in the image. Other factors may alsoaffect the luminance value scaling operation. In some embodiments, theseluminance values may be offset 94. The offset operation may also berelated to the spatial position of the luminance value. In someembodiments, the chrominance values of the decoded LDR/baselayer imagemay be scaled 95. This chrominance scaling may also be related to thespatial position of the chrominance value. In some embodiments,chrominance values may also be offset 96. The chrominance value offsetmay be related to a luminance offset, a chrominance value or scalingfactor and/or a spatial position of the chrominance value. Other factorsmay also affect the chrominance offset.

Once the luminance and chrominance values are scaled and/or offset, theymay be used to predict 97 a corresponding HDR/enhancement layer imageelement.

In some embodiments, the inter-layer prediction process may becontrolled at a fine granularity. As a specific example, the scaling andoffset factors may vary on a 4×4 block basis. That is, for every 4×4block in the image, an encoder may signal the appropriate scaling andoffset factor. Additionally, an encoder may enable and disableinter-layer prediction on a block by block basis. This allows, forexample, the high dynamic range image to be predicted from the lowdynamic range image in a portion of the frame while predicted withalternative mechanisms in other spatial regions. Specifically,intra-frame and inter-frame prediction mechanisms may be utilized inthese other spatial regions.

Exemplary Scaling Embodiments

Some embodiments of the present invention comprise inter-layerprediction methods that are multiplication free. In these embodiments,the baselayer data may be decoded and the decoded samples may beprocessed with a sequence of binary shifts and adds. In someembodiments, this may be accomplished with a process described byequation 1.

$\begin{matrix}{{{HDR}\left( {x,y} \right)} = {\sum\limits_{\forall i}{a_{i}*{{LDR}\left( {x,y} \right)}\mspace{11mu} \text{<<}\mspace{11mu} i}}} & (1)\end{matrix}$

where HDR and LDR are, respectively, the high dynamic range and lowdynamic range version of the image sequence, x and y denote the spatiallocation within the image frame, and a_(i) is a binary indicator thatbelongs to the set {−1,0,1}. Some embodiments may select i={0, 1,2,3}.

Alternative Exemplary Scaling Embodiments

Some inter-layer prediction embodiments comprise an offset in theinter-layer prediction process. Some embodiments may comprise a processdescribed in equation 2.

$\begin{matrix}{{{HDR}\left( {x,y} \right)} = {{\sum\limits_{\forall i}{a_{i}*{{LDR}\left( {x,y} \right)}\mspace{11mu} \text{<<}\mspace{11mu} i}} + {{Offset}\left( {x,y} \right)}}} & (2)\end{matrix}$

where Offset(x,y) is the offset value. In some embodiments, the offsetvalue may be signaled with the scaling values. Alternatively, it may besignaled as part of a residual refinement process.

Spatial Adaptivity

In some embodiments, control of the prediction process may be enabled atfine granularity. For example, when the baselayer video codec employs ablock based structure, the inter-layer prediction process may vary thescaling and offset parameters on a similar block grid. In someembodiments, this may be achieved by sending scaling and/or offsetinformation from the encoder to the decoder within an enhancementbit-stream.

In some signaling embodiments, the scaling factors may be transmitteddifferentially. That is, the scale factor may be predicted frompreviously received scale factors. Then, a correction may be transmittedin the bit-stream. Some embodiments may predict the scale factor fromthe upper or left-most neighbor to the current block. Alternatively,some embodiments may predict the scale factor as the minimum value ofthe upper or left-most neighbor.

In addition, in some embodiments, the encoder may signal the correctionvalue as a function of the upper and left-most neighbors. For example,the encoder and decoder may utilize a specific context or state forsignaling when the neighbors have the same scale factor. An alternativestate may be utilized when the neighbors have different scale factors.

High Level Syntax

Some embodiments of the present invention comprise high dynamic rangevideo coding where the scale factor is the same throughout an imageregion. To accommodate these cases, high level information may also betransmitted from the encoder to the decoder. This high level informationcan disable the transmission of scaling and/or offset parameters on ablock-by-block or region-by-region basis. For the case that transmissionof the parameters is disabled, the high level information may comprisethe scaling and/or offset information to be utilized. In someembodiments, this high level signaling will occur on a macroblock,slice, picture or sequence basis.

Transform Domain Processing

In some embodiments of the present invention, the inter-layer predictionprocess operates on intensity data. That is, the information is decodedand converted to the spatial domain by reversing any transform utilizedfor signaling. In alternative prediction embodiments, the scaling andoffset operations may be directly applied in the transform domain. Inthese embodiments, the transform coefficients may be de-quantized andthen scaled by scale factors. In some embodiments, transformcoefficients may be processed differently depending on their frequencycharacteristics. For example, in some embodiments, the scaling operationmay be applied solely to the AC coefficients while the offset operationmay affect the DC component. In some embodiments, different scaling andoffset operations may be signaled for different coefficients orcoefficient types.

Some embodiments of the present invention may comprise a video codecthat may adaptively switch between transform domain and spatial domainprediction mechanisms. In some embodiments, this switch may be signaledon a sequence, frame or slice basis. In some embodiments, this switchmay operate at finer granularity, such as a block or macro-block.

Color and Color Space Issues

An issue in scalable, high dynamic range video coding is the managementof color. In some embodiments of the present invention, a colortransform may be used prior to inter-layer prediction. This addressesthe fact that most color spaces utilized for video coding are notiso-luminant. For example, a video codec typically transmits data in theYCbCr color space with code word mappings defined in InternationalTelecommunication Union, “Parameter Values for the HDTV standards forproduction and international programme exchange,” ITU-R BT.709-5, April,2002.

Some embodiments of the present invention perform an inter-layerprediction process in a color space closely related to the coding colorspace. In some exemplary embodiments, the color transform may beexpressed in the following equations:

Y_(LDR) = Y_(LDR)$b = \frac{{Cb}_{LDR}}{Y_{LDR} + {Cr}_{LDR} + {Cb}_{LDR}}$$y = \frac{Y_{LDR}}{Y_{LDR} + {Cr}_{LDR} + {Cb}_{LDR}}$

where Y_(LDR), Cb_(LDR) and Cr_(LDR) are the luma and chroma componentsin the low dynamic range image sequence, respectively. Then, the scalingand offset process may be applied to Y_(LDR) to generate Y_(HDR).Finally, the inter-predicted region may be computed with the followingequations:

Y_(HDR) = Y_(HDR) ${Cb}_{HDR} = \frac{{bY}_{HDR}}{y}$${Cr}_{HDR} = \frac{\left( {1 - b - y} \right)Y_{HDR}}{y}$

where Cb_(HDR) and Cr_(HDR) are predictions for the color components inthe high dynamic range layer.

In some embodiments wherein Y_(LDR), Cb_(LDR) and Cr_(LDR) are notrepresented at the same resolution, the components may be resampled. Insome exemplary embodiments, applications may down-sample the lumacomponent when the chroma components are stored at lower resolution.Alternatively, the chroma components may be up-sampled to match theresolution of the luma component.

Alternative Color and Color Space Issues

In some embodiments of the present invention, inter-layer prediction mayoperate directly on the decoded data without employing a colortransform. In some exemplary embodiments, the prediction process may beexpressed by the following equations:

Y _(HDR)(x,y)=Scale(x,y,c)*Y _(LDR)(x,y)+Offset(x,y,c)

Cb _(HDR)(x,y)=Scale(x,y,c)*Cb _(LDR)(x,y)+Offset(x,y,c)

Cr _(HDR)(x,y)=Scale(x,y,c)*Cr _(LDR)(x,y)+Offset(x,y,c)

where the scaling and offset parameters are now a function of bothspatial location and chroma component. That is, the reconstructed lumaand chroma values are scaled with different scale factors.

In some exemplary inter-prediction processes, the luma and chroma valuesmay be scaled with the same scale factor but with different offsets.This may be expressed with the following equations:

Y _(HDR)(x,y)=Scale(x,y)*Y _(LDR)(x,y)+Offset(x,y,c)

Cb _(HDR)(x,y)=Scale(x,y)*Cb _(LDR)(x,y)+Offset(x,y,c)

Cr _(HDR)(x,y)=Scale(x,y)*Cr _(LDR)(x,y)+Offset(x,y,c)

In these embodiments, the scale factor may not depend on the chromacomponent. In some embodiments, the encoder may transmit the offsetswithin the enhancement layer bit-stream.

In other exemplary embodiments of the inter-prediction process, the lumaand chroma values may be scaled with the same scale factor and theoffset for the chroma values may be dependent on the offset of the lumavalues as well as the decoded image data. This relationship may beexpressed in the following equations:

Y _(HDR)(x,y)=Scale(x,y)*Y _(LDR)(x,y)+Offset(x,y)

Cb _(HDR)(x,y)=Scale(x,y)*Cb _(LDR)(x,y)+f(Offset(x,y),Cb _(LDR)(x,y),Y_(LDR)(x,y))

Cr _(HDR)(x,y)=Scale(x,y)*Cr _(LDR)(x,y)+f(Offset(x,y),Cr _(LDR)(x,y),Y_(LDR)(x,y))

where f( ) denotes a mapping operation.

An exemplary mapping operation may be expressed as:

${f\left( {{{Offset}\left( {x,y} \right)},{A_{LDR}\left( {x,y} \right)},{Y_{LDR}\left( {x,y} \right)}} \right)} = {{{Offset}\left( {x,y} \right)}\frac{A_{LDR}\left( {x,y} \right)}{Y_{LDR}\left( {x,y} \right)}}$

where A_(LDR)(x,y) denotes an arbitrary color component such as Cb orCr.

As mentioned before, the chroma and luma components may be representedon different sampling grids. To address this problem, the chroma andluma data may be resampled to the same resolution. In some embodiments,a different mapping process may be employed. In some exemplaryembodiments, the mapping relationship may be expressed as:

${f\left( {{{Offset}\left( {x,y} \right)},{A_{LDR}\left( {x,y} \right)},{Y_{LDR}\left( {x,y} \right)}} \right)} = {{{Offset}\left( {x,y} \right)}\frac{{Avg}\left( {A_{LDR}\left( {x,y} \right)} \right)}{{Avg}\left( {Y_{LDR}\left( {x,y} \right)} \right)}}$

where Avg( ) denotes the mean operator. In another exemplary embodiment,the mean may be replaced with a summation operation. In otherembodiments, non-linear operations such as the median, min and maxoperations may be beneficial.

In some exemplary embodiments, the mean operator (or an alternativeoperator) may be performed in a different domain than that of the Offsetvariable. In some exemplary embodiments, the mean operation may becomputed in the transform domain by operating solely on the DCcoefficient. Similarly, in embodiments wherein the spatial resolutionsof the chroma and luma coefficients are not matched, the mean operationmay be computed by analyzing multiple DC coefficients in the lumabaselayer.

The terms and expressions which have been employed in the foregoingspecification are used therein as terms of description and not oflimitation, and there is no intention in the use of such terms andexpressions of excluding equivalence of the features shown and describedor portions thereof, it being recognized that the scope of the inventionis defined and limited only by the claims which follow.

1. A method for predicting a high dynamic range image block withblock-specific prediction data, said method comprising: a) receiving lowdynamic range (LDR) image data for a target image block; b) receivinghigh dynamic range (HDR) image data for said target image block, saidHDR image data comprising an HDR residual image block, a predictionscaling factor and a prediction offset factor for said target imageblock; c) extracting an LDR image block from said LDR image data; d)scaling said LDR image block with said prediction scaling factor; e)offsetting said LDR image block with said prediction offset factor; andf) combining said scaled, offset LDR image block with said HDR residualimage block to form an HDR image block corresponding to said targetimage block.
 2. A method as described in claim 1 wherein said combiningcomprises adding image values in said scaled, offset LDR image block tocorresponding values in said HDR residual image block.
 3. A method asdescribed in claim 1 wherein said extracting comprises decoding, inversetransformation, dequantizing and prediction of said LDR image block. 4.A method for predicting a high dynamic range image block withdifferentially-coded prediction data, said method comprising: a)receiving high dynamic range (HDR) image data for a first image block,said HDR image data comprising a first HDR residual image block andfirst prediction data for said first image block; b) receiving highdynamic range (HDR) image data for a second image block, said HDR imagedata comprising a second HDR residual image block and predictiondifference data related to said first prediction data; and c) combiningsaid first prediction data and said prediction difference data todetermine second prediction data for said second image block.
 5. Amethod as described in claim 4 wherein said first image block is anupper neighbor to said second image block.
 6. A method as described inclaim 4 wherein said first image block is a neighbor to the left of saidsecond image block.
 7. A method as described in claim 4 wherein saidfirst image block is selected from a neighborhood around said secondimage block.
 8. A method as described in claim 4 wherein said firstimage block is selected as the lesser of an upper neighbor and aleft-hand neighbor to said second image block.
 9. A method as describedin claim 4 wherein said first prediction data comprises a scaling factorand an offset factor.
 10. A method for predicting a high dynamic rangeimage block with differentially-coded prediction data, said methodcomprising: a) receiving high dynamic range (HDR) image data for a firstimage block, said HDR image data comprising first prediction data forsaid first image block; b) receiving high dynamic range (HDR) image datafor a second image block, said HDR image data comprising secondprediction data for said second image block; c) receiving thirdprediction difference data for a third image block wherein said thirdprediction difference data is differentially coded relative to at leastone of said first prediction data and said second prediction data; andd) determining third prediction data for said third image block based onat least one of said third prediction difference data, said secondprediction data and said first prediction data.
 11. A method asdescribed in claim 10 wherein said second prediction data comprises adifferential quantity related to said first image data.
 12. A method asdescribed in claim 10 wherein said determining third prediction datacomprises determining a state defined by the values of said firstprediction data and said second prediction data.
 13. A method asdescribed in claim 10 wherein said first prediction data comprises ascaling factor.
 14. A method as described in claim 10 wherein said firstprediction data comprises an offset factor.
 15. A method for predictingan image, said method comprising: a) receiving a high-level predictionmessage defining prediction data for a plurality of image elementswherein said message disables transmission of element-specificprediction data for individual image elements; b) receiving high dynamicrange (HDR) image data for said plurality of image elements, said HDRimage data comprising HDR residual image blocks; and c) predicting saidplurality of image elements using data from said high-level predictionmessage.
 16. A method as described in claim 15 wherein said plurality ofimage elements comprises an image block.
 17. A method as described inclaim 15 wherein said plurality of image elements comprises an imageframe.
 18. A method as described in claim 15 further comprisingreceiving a high-level prediction message wherein said message enablestransmission of element-specific prediction data for individual imageelements.
 19. A method as described in claim 15 wherein said predictiondata defined by said high-level prediction message comprises a scalingfactor.
 20. A method as described in claim 15 wherein said predictiondata defined by said high-level prediction message comprises an offsetfactor.